The present invention relates to Built-In-Self Repair schemes and controllers for Built-In-Self Repair designs.
Built-in-Self-Repair (BISR) is a scheme wherein a certain amount of redundant elements are provided in each memory so that random process defects do not cause excessive yield loss. As shown in FIG. 1, current widely-used versions of BISR run different patterns at wafer-level to test the memories on the chip (box 10 in FIG. 1) and generate a repair solution which can be scanned out of the chip (via the flarescan mode) and written to an output file (box 12 in FIG. 1). The repair solutions are then programmed on the respective devices by blowing fuses (box 14 in FIG. 1). Thereafter, a power-on state machine (on-chip) repairs the memories (box 16 in FIG. 1). The power-on state machine runs a BISR mode called fusescan which loads the fuse values into the memories. This repairs the memories (soft-repair) after which they can be accessed in the functional mode.
However, with the current hard-BISR scheme, once the fuses are blown, there is no ability to rerun the BISR and repair any new failures that might occur during the life-time of the device. The repair is constrained to the information stored in the fuses.
Generally, memory contents have been increasing, and memories have higher defect densities than logic. As such, BISR is generally used in designs with large memory contents to repair defective memories. Parts which are repaired are prone to have higher reliability problems (DPM—defects per million). However, many companies which insist on certain reliability goals do not prefer to concede on DPM goals. Hence, it becomes necessary to screen these devices so as to reject the ones that exceed a certain threshold of repair beyond which they might pose a reliability risk over the lifetime of that device. The existing method requires that the repair solutions be logged to a file, and then post-processed to determine the extent of repair on each device and then screen out the ones that exceed a certain threshold. This takes time and often requires very extensive post-processing of data or maintaining complex production processes.